Visualization of water flow around different bluff bodies at different Reynolds number ranging (1505 - 2492) was realized by designing and building a test rig which contains an open channel capable to ensure water velocity range (4-8cm/s) in this channel. Hydrogen bubbles generated from the ionized water using DC power supply are visualized by a light source and photographed by a digital camera. Flow pattern around a circular disk of (3.6cm) diameter and (3mm) thickness, a sphere of (3.8cm) diameter and a cylinder of
(3.2cm) diameter and (10cm) length are studied qualitatively. Parameters of the vortex ring generated in the wake region of the disk and the separation angle of water stream lines from the surface of the sphere are plott

Objectives: ٨ descriptive study has been conducted in the premature baby unit in Al-Khansaa' and Al-Batool
hospitals for maternity and children in Mosul city to assess knowledge and practice of the nursing staff in the
caring of premature infants. A descriptive study has been conducted in the premature baby unit in Al-Khansaa'
and Al-Batool hospitals for maternity and children in Mosul city to assess knowledge and practice of the nursing
staff in the caring of premature infants.
Methodology: the data were collected by using knowledge assessment and practice measurement tool.
Results: the results of the study show that high percentages (about 40%) of the staff who work in the premature
baby units are of the young age

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Previously, many empirical models have been used to predict corrosion rates under different CO₂ corrosion parameters conditions. Most of these models did not predict the corrosion rate exactly, besides it determined effects of variables by holding some variables constant and changing the values of other variables to obtain the regression model. As a result the experiments will be large and cost too much. In this paper response surface methodology (RSM) was proposed to optimize the experiments and reduce the experimental running. The experiments studied effects of temperature (40 – 60 °C), pH (3-5), acetic acid (HAc) concentration (1000-3000 ppm) and rotation speed (1000-1500 rpm) on CO₂ corrosion performance of t

The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w

This paper presents a numerical simulation of the flow around elliptic groynes by using CFD ‎software. The flow was simulated in a flume with 4m long, 0.4m wide, ‎and 0.175m ‎high ‎‎with a constant bed slope. Moreover, the first Groyne placed at 1m from the flow ‎‎inlet with a ‎constant the Groyne height of 10cm and a 1cm thickness, and the ‎width of Groynes equals ‎7cm‎. A submergence ratio of the elliptic Groynes of 75% was assumed, corresponding to a discharge of ‎0.0057‎m³/sec. The CFD ‎model showed a good ability to simulate the flow ‎around ‎Groynes with ‎ good accuracy. The results of ‎CFD software showed that when using double elliptic Groy

In the present work, a closed loop circulation system consist of three testing sections was designed and constructed. The testing sections made from (3m) of commercial carbon steel pipe of diameters(5.08, 2.54 and 1.91 cm) . Anionic surfactant  (SDBS )with  concentrations  of (50,  100,  150, 200 and 250 ppm)  was tested as a drag reducing  agent.  The additive(SDBS)studied using crude oil from south of Iraq. The flow rates of crude oil were used in 5.08 and 2.54 cm I.D. pipes are (1 - 12) m³/hr while (1-6) m3/hr were used in 1.91 cm J .D. pipe . Percentage drag reduction (%Dr) was found to increase by increasing solution velocity, pipe diameter and additives concentration (i.e. increasi

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a